In [1]:
import pandas as pd
In [2]:
import numpy as np
In [3]:
import pandas_profiling.model.pandas
In [4]:
df=pd.read_csv("data.csv.zip")
In [5]:
df.head()
Out[5]:
valence year acousticness artists danceability duration_ms energy explicit id instrumentalness key liveness loudness mode name popularity release_date speechiness tempo
0 0.0594 1921 0.982 ['Sergei Rachmaninoff', 'James Levine', 'Berli... 0.279 831667 0.211 0 4BJqT0PrAfrxzMOxytFOIz 0.878000 10 0.665 -20.096 1 Piano Concerto No. 3 in D Minor, Op. 30: III. ... 4 1921 0.0366 80.954
1 0.9630 1921 0.732 ['Dennis Day'] 0.819 180533 0.341 0 7xPhfUan2yNtyFG0cUWkt8 0.000000 7 0.160 -12.441 1 Clancy Lowered the Boom 5 1921 0.4150 60.936
2 0.0394 1921 0.961 ['KHP Kridhamardawa Karaton Ngayogyakarta Hadi... 0.328 500062 0.166 0 1o6I8BglA6ylDMrIELygv1 0.913000 3 0.101 -14.850 1 Gati Bali 5 1921 0.0339 110.339
3 0.1650 1921 0.967 ['Frank Parker'] 0.275 210000 0.309 0 3ftBPsC5vPBKxYSee08FDH 0.000028 5 0.381 -9.316 1 Danny Boy 3 1921 0.0354 100.109
4 0.2530 1921 0.957 ['Phil Regan'] 0.418 166693 0.193 0 4d6HGyGT8e121BsdKmw9v6 0.000002 3 0.229 -10.096 1 When Irish Eyes Are Smiling 2 1921 0.0380 101.665
In [6]:
!pip install https://github.com/pandas-profiling/pandas-profiling/archive/master.zip

Collecting https://github.com/pandas-profiling/pandas-profiling/archive/master.zip
  Using cached https://github.com/pandas-profiling/pandas-profiling/archive/master.zip (21.9 MB)
  Preparing metadata (setup.py): started
  Preparing metadata (setup.py): finished with status 'done'
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In [9]:
from pandas_profiling import ProfileReport
In [11]:
profile = ProfileReport(df,title="data analysis",html={ "style":{"ful_width":True}})
#profile.to_file(output_file="data analysis.html")
In [12]:
profile

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Out[12]:
























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